|
|
Absolute deviation, 绝对离差% p/ I3 o% ?: d% f/ m
Absolute number, 绝对数
7 I# M+ V0 w- H4 G& ~& P& BAbsolute residuals, 绝对残差
: @: m* ^' @" f7 [8 D$ hAcceleration array, 加速度立体阵4 h z. S3 E% Y' T& g+ S1 p9 M2 s; n
Acceleration in an arbitrary direction, 任意方向上的加速度9 O; \' U* G% `0 h& P/ J5 a# Y
Acceleration normal, 法向加速度- i* w- j( k5 z
Acceleration space dimension, 加速度空间的维数 D0 y" H) z( x( T) Z, x
Acceleration tangential, 切向加速度
5 c' s8 d. D/ i8 N. Q6 u7 RAcceleration vector, 加速度向量5 m6 K) [4 R! E$ H( r6 B
Acceptable hypothesis, 可接受假设( J0 F: ]# {9 A& V' [
Accumulation, 累积
3 V3 Z5 G$ s, N7 w1 l# lAccuracy, 准确度
) Q+ w) H) `- o; L" a# k9 FActual frequency, 实际频数5 Z; x3 T/ _ `: l
Adaptive estimator, 自适应估计量
$ e& W5 j6 h! Y- B4 @ J3 \5 y, PAddition, 相加
5 p; H2 q e0 o6 }6 i# cAddition theorem, 加法定理( g0 j8 {9 U, N) ?
Additivity, 可加性
D2 ^! p3 c" f, |: i( I A DAdjusted rate, 调整率
; S" Y: w1 C7 K" V) ?2 V! fAdjusted value, 校正值
. b& y& F y$ V9 `" c# gAdmissible error, 容许误差
- _1 k. ^- w5 z; P( f4 GAggregation, 聚集性
) k E- f1 N% q8 D1 e3 E, HAlternative hypothesis, 备择假设
7 E) f8 U% X. W) I& BAmong groups, 组间+ L3 W# J+ s* G7 R+ N0 U
Amounts, 总量% \9 q! B3 Y- }, J
Analysis of correlation, 相关分析
1 y) H E) t8 N. ^1 H- ~% IAnalysis of covariance, 协方差分析
6 b* c4 f7 {6 H3 ^) _+ T7 qAnalysis of regression, 回归分析$ [% v' a) t) v1 c8 x% Q0 U
Analysis of time series, 时间序列分析: _0 `' L! _( @8 N4 B
Analysis of variance, 方差分析
) @7 M2 t2 X. u+ E# ^Angular transformation, 角转换' D* K$ f! H5 T: W( _
ANOVA （analysis of variance）, 方差分析
; G7 C. X' G _2 u; BANOVA Models, 方差分析模型
3 I) P. ?0 B1 y5 |: |$ z5 EArcing, 弧/弧旋
$ @6 S' E, q! V' x; @/ k i$ EArcsine transformation, 反正弦变换
o/ m6 f+ p* ^Area under the curve, 曲线面积
0 _0 W5 a( y& ~' PAREG , 评估从一个时间点到下一个时间点回归相关时的误差
" ] n! x' }8 ]) ]2 \ARIMA, 季节和非季节性单变量模型的极大似然估计
0 J* V( w A% E% TArithmetic grid paper, 算术格纸 Y! u9 g6 I) c4 G" o. k
Arithmetic mean, 算术平均数
" T% d5 C% w: e, f! a! { W4 zArrhenius relation, 艾恩尼斯关系
v2 l5 K+ ?1 S0 P/ q6 R2 G- OAssessing fit, 拟合的评估
$ e- Q Z" B6 G5 YAssociative laws, 结合律9 z& w$ R$ Q* R' q
Asymmetric distribution, 非对称分布& z. U2 M w% d
Asymptotic bias, 渐近偏倚* o- u, j# }7 k( w4 H( s
Asymptotic efficiency, 渐近效率0 t' D3 ?7 C' K( c. L
Asymptotic variance, 渐近方差
! p" k3 S0 E$ W3 Y8 ZAttributable risk, 归因危险度
& o4 i. v/ H8 f2 g! I wAttribute data, 属性资料
2 u1 b4 w' l% C5 t5 h3 aAttribution, 属性
, J1 z7 c9 ?" w5 C7 \0 \, {) ~/ ]Autocorrelation, 自相关, b1 A) t7 L7 x
Autocorrelation of residuals, 残差的自相关
- Q3 g2 D/ B' C- SAverage, 平均数
, H5 Q& ]/ g) G& p2 I" R# n r" Q$ R, [Average confidence interval length, 平均置信区间长度
+ E2 g3 Q" ~$ J9 M1 H2 YAverage growth rate, 平均增长率
2 R* y5 _; U5 z3 X; m1 [9 Y nBar chart, 条形图
. ]1 D. a7 E4 |Bar graph, 条形图7 _4 l" o, U2 s: W
Base period, 基期
) V& i/ i. \! w( G3 B6 x* C' sBayes' theorem , Bayes定理
4 S# V% @2 o e- MBell-shaped curve, 钟形曲线
* `! D6 F$ [3 x- kBernoulli distribution, 伯努力分布
; E n" J. r2 _' W9 H) s4 K) kBest-trim estimator, 最好切尾估计量
g7 Q9 D0 v% C3 W7 E5 HBias, 偏性2 \# g2 l& z8 q/ Y
Binary logistic regression, 二元逻辑斯蒂回归
6 h$ Y/ g3 i6 @$ P& xBinomial distribution, 二项分布5 I+ j- p$ ~+ k) n4 D+ N+ S; ?
Bisquare, 双平方' }" ^/ _' [3 n2 g
Bivariate Correlate, 二变量相关& V/ _9 E8 Y2 K) ^% |
Bivariate normal distribution, 双变量正态分布
, C. L5 j' I- U; A( G; JBivariate normal population, 双变量正态总体
% L# v" @3 N. q+ OBiweight interval, 双权区间) @! N( A% _& H+ c- G1 s- h5 l y
Biweight M-estimator, 双权M估计量
2 X, G9 f9 r7 H3 ^- H- @Block, 区组/配伍组2 Q" Y2 y4 q% S2 l
BMDP(Biomedical computer programs), BMDP统计软件包) n5 A3 `! b1 D' \9 Z( ?7 V9 n! D9 [
Boxplots, 箱线图/箱尾图' w% @2 {$ W1 @) E0 y
Breakdown bound, 崩溃界/崩溃点# W) s' w5 ~/ `8 L/ g8 R
Canonical correlation, 典型相关
% \0 I5 a8 M: x( C" [$ e [Caption, 纵标目
1 g; \+ I. ]5 C# w3 D6 JCase-control study, 病例对照研究4 w/ x4 l. j# P
Categorical variable, 分类变量
0 e+ ?4 d/ A) L7 w1 d! p1 A$ YCatenary, 悬链线7 g- ]$ r* q, j/ w6 B1 b) P3 \
Cauchy distribution, 柯西分布
3 W" ~6 n" z: X- z7 X# B0 F- TCause-and-effect relationship, 因果关系4 F& z. A+ U' v& y+ X3 ~; e
Cell, 单元- \! `! F; S/ v
Censoring, 终检
: d) l" Y }/ PCenter of symmetry, 对称中心
0 H- A0 b/ ^" j4 j# K5 DCentering and scaling, 中心化和定标. O5 _: D/ Z) j/ G) J* b) s# P
Central tendency, 集中趋势
8 J7 @/ N6 p, E% I0 ^ U% LCentral value, 中心值
2 b; ~- A7 i! v& h0 _8 vCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测$ C! R; H* w ]
Chance, 机遇2 T W+ H1 t% y, S
Chance error, 随机误差
3 \0 X- S( e# jChance variable, 随机变量
7 ^: G- k8 F6 o T bCharacteristic equation, 特征方程
1 p/ z/ ]- L* o rCharacteristic root, 特征根
# W' H7 o9 H( T8 W) `Characteristic vector, 特征向量
: { Q; w; D# z- TChebshev criterion of fit, 拟合的切比雪夫准则+ M6 I( i( C/ P: p
Chernoff faces, 切尔诺夫脸谱图" Y# `% p- r! W9 ^! Q
Chi-square test, 卡方检验/χ2检验
& L$ f% }' c+ s4 m- i2 x2 [Choleskey decomposition, 乔洛斯基分解
0 v6 r, V* k5 wCircle chart, 圆图
8 ^+ U- z8 I* _" I5 G( ?+ V9 r* [Class interval, 组距
J( h6 w8 ]9 E) x/ p% uClass mid-value, 组中值
" N G. O% C& w RClass upper limit, 组上限
+ A5 T1 a( V0 J7 z9 hClassified variable, 分类变量
0 A8 c0 I% l3 Y, [Cluster analysis, 聚类分析
9 s0 |, ~ l8 \8 y: c x* i _( H) MCluster sampling, 整群抽样
" J# _2 o F; E2 A- V0 ?Code, 代码& c; w3 v! C. w$ z* m: \3 @% ^
Coded data, 编码数据
) m _/ C/ x. M+ |1 G3 b+ mCoding, 编码 J5 Z$ o( h- e/ E6 X
Coefficient of contingency, 列联系数# Q4 X1 k( ^# t
Coefficient of determination, 决定系数; Z$ R3 i* |- N# O- b) D* h5 L C
Coefficient of multiple correlation, 多重相关系数; L, K6 w0 o. P) }
Coefficient of partial correlation, 偏相关系数! W: ~ o9 z" Y+ `& p/ A0 O) q: C. _
Coefficient of production-moment correlation, 积差相关系数
$ C0 V& y- D; j' E, v5 l3 V6 F- w0 eCoefficient of rank correlation, 等级相关系数
6 I3 `' U" u5 S& N, Z8 ]9 JCoefficient of regression, 回归系数0 C, l9 z+ a2 ~5 J" z0 w. j* s
Coefficient of skewness, 偏度系数4 t; ^3 d( e8 H
Coefficient of variation, 变异系数0 w) G% v& w) N* `9 z/ O3 q0 ]( y# B
Cohort study, 队列研究$ m: J5 B6 t. j; H
Column, 列
0 ^+ w' {- }7 [# |7 V& Z5 aColumn effect, 列效应
: v; K2 h2 y! a8 r( LColumn factor, 列因素* N" t( @* B7 i6 ?5 T
Combination pool, 合并8 {$ `( C2 G: h. A- J- e% V
Combinative table, 组合表+ N. Z6 i+ I ]: P7 y5 O
Common factor, 共性因子
6 x, N, A2 y! m- t% {: v1 H2 uCommon regression coefficient, 公共回归系数" Q1 K5 I' o: c- @5 F
Common value, 共同值. ?2 s( K+ w& }8 V9 g. J& I
Common variance, 公共方差4 u1 K- S& u4 o: S$ D7 o. g
Common variation, 公共变异
3 t7 Z1 e* C4 w4 o& J& rCommunality variance, 共性方差
2 [7 w0 L- c8 m/ Y/ wComparability, 可比性: `( |$ X/ Q0 N+ L* ?
Comparison of bathes, 批比较
9 U8 k2 J! v+ S/ P" c6 M. DComparison value, 比较值4 Z6 z- M, w N3 q2 L; h- g) u
Compartment model, 分部模型
8 v' \& t, S% w* B6 sCompassion, 伸缩4 i$ H2 ?+ B. r; Z
Complement of an event, 补事件
6 ~/ P) n# n9 O6 \ A7 \3 q. B E% RComplete association, 完全正相关
# U$ V* l; t0 R2 Z }) F4 `, O: GComplete dissociation, 完全不相关 C5 d! s9 K* x/ v* w
Complete statistics, 完备统计量. P0 m2 m$ X4 p& J2 @( Q4 C
Completely randomized design, 完全随机化设计
) R9 U7 u2 I1 i6 o- dComposite event, 联合事件
- R( }8 W' h$ i P8 x9 T6 pComposite events, 复合事件% ]: N" \& _6 l6 L6 a- y0 s5 G
Concavity, 凹性 t7 ?2 W% {/ T5 @7 `+ y
Conditional expectation, 条件期望
( |" ?; O! q8 EConditional likelihood, 条件似然% p. S/ e3 ?/ w
Conditional probability, 条件概率
5 b+ H+ a! k. vConditionally linear, 依条件线性
. P7 _. D) T7 f+ E3 s! T% EConfidence interval, 置信区间, b. c7 ~! A3 g7 l' w2 s h
Confidence limit, 置信限
/ ^0 R# h( v1 H$ q( q3 z" K" x% UConfidence lower limit, 置信下限+ X5 ~* R0 ?3 k$ N2 _4 I; r( m
Confidence upper limit, 置信上限* K) Z: [* e' q, }
Confirmatory Factor Analysis , 验证性因子分析) C, ~2 u( U" h
Confirmatory research, 证实性实验研究
* Y+ p$ Q) p- ]Confounding factor, 混杂因素# f) w0 F. p8 E9 g
Conjoint, 联合分析2 V4 \# Q# ^$ g* k
Consistency, 相合性
7 @8 L( U4 [# A7 `; k- VConsistency check, 一致性检验# M8 M$ X3 X* S
Consistent asymptotically normal estimate, 相合渐近正态估计' ~1 Q& O+ G# O/ ^
Consistent estimate, 相合估计1 j: }" ^. P8 [& I
Constrained nonlinear regression, 受约束非线性回归8 Z, G5 t; p" j( ` G
Constraint, 约束% @9 Q( q* Q$ S+ _6 ^
Contaminated distribution, 污染分布
. t4 P, [! c3 X+ S$ {1 K5 w. AContaminated Gausssian, 污染高斯分布
1 J' H1 k" f" r l- L* O- S% t8 A; lContaminated normal distribution, 污染正态分布$ J4 G9 K; R( b' y/ r4 o$ A- ^
Contamination, 污染- p+ S0 }- ]9 d9 q6 a( s
Contamination model, 污染模型
: a" h1 a+ r! @Contingency table, 列联表4 F" ~. K2 n* \. k! c! L* ]
Contour, 边界线7 s, W- d' Z8 Q& S+ P. ?
Contribution rate, 贡献率+ d' c3 ]4 P0 ]
Control, 对照
1 Z: l6 g# L7 ~& }7 bControlled experiments, 对照实验4 Z6 z5 B8 l: c3 G& m8 G
Conventional depth, 常规深度
9 X$ g1 {4 G& h, p/ E6 RConvolution, 卷积
3 ~3 f# E- ~' @" O6 J: L& c# x$ wCorrected factor, 校正因子
" c ^9 G+ q! Q! `; ~) JCorrected mean, 校正均值
6 O J9 v. e6 K4 q: G& [ L' R5 R0 xCorrection coefficient, 校正系数" N+ m7 G0 w) v. A# K1 H
Correctness, 正确性* R) @; o8 Q# V
Correlation coefficient, 相关系数$ ~, n1 f. _) |9 F
Correlation index, 相关指数% j2 _5 A# r1 c: f
Correspondence, 对应' J9 w! k. O3 X6 N& I3 q/ a
Counting, 计数
/ Y: i' z8 G4 V" xCounts, 计数/频数8 l* Q! c- p8 k: U" H
Covariance, 协方差; \- q1 a! e. b |4 h
Covariant, 共变 " W" K8 x, r1 q- U, ?* x
Cox Regression, Cox回归: E7 h( a3 `+ _
Criteria for fitting, 拟合准则
- ^: R# L* M" [, R+ s. CCriteria of least squares, 最小二乘准则1 \- N/ P$ d) ^ \, ?
Critical ratio, 临界比# [2 j7 j {' j5 h0 U2 P& y
Critical region, 拒绝域
* M4 T/ r1 c/ @Critical value, 临界值, @% T7 [* {6 c: I
Cross-over design, 交叉设计" A2 Q: X- c1 d& {
Cross-section analysis, 横断面分析
; \2 I+ o; d# ~8 B+ y' d/ M8 J- a' ECross-section survey, 横断面调查
, g y5 F4 ?, G9 ?( Z2 kCrosstabs , 交叉表
& a, q U! c; D6 ~; h4 gCross-tabulation table, 复合表
) @) O, i7 z u7 h9 s1 ~Cube root, 立方根$ q) h j0 p! ?
Cumulative distribution function, 分布函数5 }$ C* X/ F1 X1 V+ U% T0 A
Cumulative probability, 累计概率) ^* ^2 e7 [& W: m+ p
Curvature, 曲率/弯曲
" ~1 K+ K) E5 [$ V. QCurvature, 曲率
; L6 ]3 r$ P+ z/ ~: e+ O* vCurve fit , 曲线拟和
1 }9 q8 R. [' l3 ?3 _, VCurve fitting, 曲线拟合
2 n D0 P& {4 a5 f1 A4 PCurvilinear regression, 曲线回归& e/ [2 T$ P; i1 Z# F- O
Curvilinear relation, 曲线关系9 Z# }% `2 A$ g1 T% [8 x; l8 K8 ~
Cut-and-try method, 尝试法
$ M6 e; q# C1 V5 o( aCycle, 周期
/ |, J% s3 C: r" T, W; ~% @Cyclist, 周期性9 u) ?# J. Z4 m
D test, D检验
. O$ V0 [* T1 E. S% j$ }. Y: z# WData acquisition, 资料收集
9 m: r4 c) }* }: @* H3 dData bank, 数据库0 l- J9 B# N1 x7 r4 K
Data capacity, 数据容量. U6 b6 c; U ^& D
Data deficiencies, 数据缺乏
: N2 y! o0 j- }- e3 H, L0 _Data handling, 数据处理
: Q" M/ _' o$ t) B4 m9 LData manipulation, 数据处理0 J2 T! l- M: J/ m5 L$ D! g% v9 |
Data processing, 数据处理
n* `% k. M$ U6 t" SData reduction, 数据缩减0 h. R; N, _. X
Data set, 数据集
; D+ v8 }) g$ M H, rData sources, 数据来源
) W+ P1 ^4 M( mData transformation, 数据变换! A/ _! D3 _- o* U( M. y, a' F
Data validity, 数据有效性
; x0 n! ~, m% U. _ |3 qData-in, 数据输入: P) L0 y" f! O: n5 ?
Data-out, 数据输出$ F" M* R2 Z C4 T6 g* {
Dead time, 停滞期# l: U7 K% L( {& u; g! X
Degree of freedom, 自由度- @, ?4 f% e, J# L6 w
Degree of precision, 精密度7 J0 {. ^7 f& o: \0 h h
Degree of reliability, 可靠性程度
# ~! P( e. i% Q5 Y0 k4 l$ M: rDegression, 递减
. O% \1 u. Q$ S: ADensity function, 密度函数5 y' A/ K3 A4 @' t: {
Density of data points, 数据点的密度! s, @0 K6 R, B1 t+ }0 k
Dependent variable, 应变量/依变量/因变量, J: e }4 c* x9 _; y2 Q& a; _ }
Dependent variable, 因变量/ s! i) j/ c! y3 z/ }1 [! j
Depth, 深度
2 b1 u( [ j; JDerivative matrix, 导数矩阵
% z9 ]- X' ^' `9 D( G# CDerivative-free methods, 无导数方法
1 n: z1 p& {6 s% L1 N% `Design, 设计
# K, q- M- B7 B) `; F0 rDeterminacy, 确定性/ ~1 p4 h3 i/ T" n0 S G: n
Determinant, 行列式/ w N( m e0 H" j" A5 u
Determinant, 决定因素* p. _% V2 R! z# h0 l
Deviation, 离差7 ]) A6 z; h, ]+ N/ s$ ?
Deviation from average, 离均差
: C3 _/ A/ i) `3 S7 j( K, ^Diagnostic plot, 诊断图
6 {& J+ e( \! l8 nDichotomous variable, 二分变量% l& O$ g: S+ U i: y* ?0 h, b
Differential equation, 微分方程$ y! r; a6 S+ q* h7 \+ P3 L3 z
Direct standardization, 直接标准化法
' W0 A" ^: N0 xDiscrete variable, 离散型变量
C2 W+ j9 N) K2 g- kDISCRIMINANT, 判断 ' w# Q$ k- h9 Y
Discriminant analysis, 判别分析! Y0 {5 x/ c* l( v7 N
Discriminant coefficient, 判别系数
* r/ E% e3 p. S: |) ]! a! {Discriminant function, 判别值! d, I& S- x, C+ i
Dispersion, 散布/分散度! D9 k' j2 q# h% a
Disproportional, 不成比例的6 G+ T {7 }/ w
Disproportionate sub-class numbers, 不成比例次级组含量* _+ G2 C3 g9 [- G8 u* s9 ^
Distribution free, 分布无关性/免分布+ a1 T, @# u* _& [% ]
Distribution shape, 分布形状
& B" @ V3 F! Y5 O8 i- ]+ XDistribution-free method, 任意分布法
7 H4 d4 t+ z! z3 P3 F' a) zDistributive laws, 分配律
2 I' M$ j+ O2 Z6 ^- D3 Z+ PDisturbance, 随机扰动项
8 L9 A% x) X# t$ e% K0 ADose response curve, 剂量反应曲线: x- d s2 k5 Q) b O
Double blind method, 双盲法
9 m5 x+ h3 ] ?- J; O4 XDouble blind trial, 双盲试验3 _: }7 V0 c2 P. z2 g6 b
Double exponential distribution, 双指数分布
) C0 k2 O5 u9 [Double logarithmic, 双对数
- b X" B" I# ^. A- `Downward rank, 降秩! D+ [+ Y1 s" T6 G8 }- h
Dual-space plot, 对偶空间图6 }2 ]6 P3 M. c. v% U2 y5 X
DUD, 无导数方法
; @* {7 U1 Y: I" q, x- ~9 HDuncan's new multiple range method, 新复极差法/Duncan新法
* G, v" }8 @& s! r- _9 iEffect, 实验效应
% g5 @" x/ {. j2 J# F$ pEigenvalue, 特征值! {0 }0 q2 i1 B; K5 b3 C: l3 Z
Eigenvector, 特征向量5 p, a9 R7 [$ E5 V* J3 i" M
Ellipse, 椭圆
y. M# A0 N2 \9 a( w( A/ L% c& ^Empirical distribution, 经验分布8 K3 `0 n% l/ B& N- L( I# [
Empirical probability, 经验概率单位
' {* o0 h# G7 [+ o( R. jEnumeration data, 计数资料4 L0 t( J0 h9 ]
Equal sun-class number, 相等次级组含量9 c$ S( Z. {" q# N" [" i/ B9 U
Equally likely, 等可能4 D. y0 ]! B$ n: I" p
Equivariance, 同变性/ w" c8 _ A! e' b) }* p
Error, 误差/错误% K' `. q& L& J: v8 u ^7 R
Error of estimate, 估计误差/ N" `( t- J0 Y3 S( ]( D& W- T# T& U e
Error type I, 第一类错误
, C3 ^' J' h/ T. |Error type II, 第二类错误
2 G. n9 ~! `; R, r( |( PEstimand, 被估量
$ D& i5 ~' B. F8 z4 R/ R, Y" @Estimated error mean squares, 估计误差均方
0 J7 v) h, i# M/ _0 `0 kEstimated error sum of squares, 估计误差平方和
6 A' z3 }# I: H6 m0 B+ ^: N9 kEuclidean distance, 欧式距离
1 N8 ?5 T! t+ G9 x$ p" b$ y' vEvent, 事件' {: w& j# }$ b
Event, 事件0 Z2 }( ~. H0 k* N a* F
Exceptional data point, 异常数据点& ~2 l0 h9 @; B
Expectation plane, 期望平面
, L" J) ?3 L; V. h) S0 G) gExpectation surface, 期望曲面4 z4 |3 E( \' ^# v
Expected values, 期望值
9 M6 F/ g4 q* }6 Y- B* a& f$ g jExperiment, 实验4 Z" i9 a6 k1 b+ D7 f0 L4 N
Experimental sampling, 试验抽样' l/ ? W* w+ i/ }7 j2 l1 ~9 V2 ^
Experimental unit, 试验单位3 _: I2 \7 ^- g, A
Explanatory variable, 说明变量6 h: s& v' w6 i
Exploratory data analysis, 探索性数据分析
9 y4 X R! p# K; QExplore Summarize, 探索-摘要
" n! Z" w: Z _* EExponential curve, 指数曲线
8 U. q/ F( l' R, OExponential growth, 指数式增长0 c) l5 c. v' ~2 [. ?
EXSMOOTH, 指数平滑方法 1 `! q# t3 b5 M# K, w, ?
Extended fit, 扩充拟合
$ W2 v8 t4 c. g" yExtra parameter, 附加参数3 M, F. e8 b c1 D3 D- ~
Extrapolation, 外推法
- a" `- i0 V% y+ ~: yExtreme observation, 末端观测值# y( }. ]+ Y8 d! X. V; _
Extremes, 极端值/极值" Q: b- P0 D2 }7 ~
F distribution, F分布
; d$ v; H) V$ E% N I- a; S/ ^F test, F检验$ W( n: X. c0 x- t" X$ \
Factor, 因素/因子% k" j3 P, E2 Q1 E: y
Factor analysis, 因子分析/ C+ P/ w8 ~8 Y
Factor Analysis, 因子分析5 l2 l# }2 ]2 i+ I3 `
Factor score, 因子得分
! r8 x) C- k7 ^( SFactorial, 阶乘: B2 ^* z2 Q- N2 d% D
Factorial design, 析因试验设计
* A% N& X8 o: x7 p7 L' EFalse negative, 假阴性
+ Z2 v; J0 w$ G# @" p: b' CFalse negative error, 假阴性错误
; N* m- M4 h4 |9 iFamily of distributions, 分布族0 @% @ z- ~0 [8 g8 y' S
Family of estimators, 估计量族
! U1 x1 y% C+ [0 f. b6 HFanning, 扇面: [# V U) I8 W3 g& G8 k0 l
Fatality rate, 病死率
: H0 Q( s# l. t, l0 ]- A; f1 l& |Field investigation, 现场调查
g. Y1 h6 _1 r9 a" F; s* wField survey, 现场调查( q- L2 M( d% V
Finite population, 有限总体$ W* W2 E9 s- L; J% [& [
Finite-sample, 有限样本
- V% ^% `$ q2 dFirst derivative, 一阶导数. p g# G5 z, E$ l
First principal component, 第一主成分& W: }! A/ t; B- b! M2 ?$ w5 K
First quartile, 第一四分位数
6 Y/ w. y! Z3 b+ t# W( uFisher information, 费雪信息量
* H7 @8 Y4 c; C% B6 gFitted value, 拟合值
7 ^' v4 [: y' G9 zFitting a curve, 曲线拟合
" h- [$ j( i. R$ H( M, v* t, fFixed base, 定基& n' w+ M+ E& g$ W: W8 W
Fluctuation, 随机起伏
8 u9 |- ]- g" s: UForecast, 预测
+ R. I5 ~3 [6 T7 F% f* x) ` j' LFour fold table, 四格表. Y! Z/ w0 X2 {
Fourth, 四分点& a2 e2 f( {$ B/ B0 }" b
Fraction blow, 左侧比率8 |8 f+ h0 t) m8 @: J/ ]
Fractional error, 相对误差
8 A1 V" Z" h; L* IFrequency, 频率$ ~) s9 [" L1 O; I! w, m' [, ~& b2 Y
Frequency polygon, 频数多边图& z3 v: T B3 E! S" P5 u6 h6 z
Frontier point, 界限点& P4 g* ~+ J3 v. h3 k' B
Function relationship, 泛函关系% }& ]* `7 {1 O) h8 L/ a# x
Gamma distribution, 伽玛分布0 L! \# @6 @* w9 {
Gauss increment, 高斯增量
% I2 M2 c9 f5 `. B3 d: CGaussian distribution, 高斯分布/正态分布8 `9 ~$ D0 M& M4 A" E9 D
Gauss-Newton increment, 高斯-牛顿增量" D% `0 l) d& C6 f" s
General census, 全面普查
' }* D* X: O1 o- s/ E8 q9 cGENLOG (Generalized liner models), 广义线性模型
8 a: r2 U" r; Q2 H& b3 EGeometric mean, 几何平均数8 G8 S2 P9 \2 b3 z
Gini's mean difference, 基尼均差
6 m$ n8 S- l6 V4 j) h" M6 mGLM (General liner models), 一般线性模型 , r+ M0 V; s7 z' i8 a) t
Goodness of fit, 拟和优度/配合度
+ E; U! F7 K3 L& a0 DGradient of determinant, 行列式的梯度
6 k# M9 L! r5 h3 k1 r& IGraeco-Latin square, 希腊拉丁方% I3 a7 V- |5 w9 B; O
Grand mean, 总均值
7 N1 Z. O; L1 WGross errors, 重大错误
5 @9 E8 Q2 Q* B/ e9 q' y3 DGross-error sensitivity, 大错敏感度) B! ?+ M4 k" h' g5 b D \
Group averages, 分组平均
% O2 P/ @5 I5 ~' Q4 e0 _Grouped data, 分组资料1 P( }) u/ ^' Q6 a0 d1 f# I' P* E" t
Guessed mean, 假定平均数
9 m* W! R+ ^% BHalf-life, 半衰期
) @+ {7 r, m* ^1 c7 k5 t' dHampel M-estimators, 汉佩尔M估计量
# I% y4 C( h" eHappenstance, 偶然事件& D% @- d! L8 [& j( `! l
Harmonic mean, 调和均数4 v- G: g# j+ ] p# m a+ `
Hazard function, 风险均数, ^# W6 v4 X2 O
Hazard rate, 风险率+ E! r& L+ v4 [1 l
Heading, 标目
& W2 @+ m j% c& T5 O+ tHeavy-tailed distribution, 重尾分布
' H# I1 Q- K& O' w3 [7 [$ AHessian array, 海森立体阵0 |' j2 [$ ~; C9 m
Heterogeneity, 不同质
0 o" T- R. \: S* @Heterogeneity of variance, 方差不齐
" N; m$ D: m7 {% L2 M5 x# c) gHierarchical classification, 组内分组( T/ o- l4 U/ Q* r
Hierarchical clustering method, 系统聚类法- ~* z/ T4 B& j* H; b5 \* W
High-leverage point, 高杠杆率点: v. w; o5 S$ o+ `/ v" Z: W
HILOGLINEAR, 多维列联表的层次对数线性模型! ?0 l H8 X/ ?
Hinge, 折叶点* B! w' v& y' K* x. v
Histogram, 直方图
1 Y7 R" \& M: [3 L) R+ MHistorical cohort study, 历史性队列研究
) R ]+ [, M T4 i6 U% D5 ?: M' BHoles, 空洞
6 ~ ]/ |" A. z hHOMALS, 多重响应分析
" n: o8 A3 r+ f$ M' P3 WHomogeneity of variance, 方差齐性* G6 \" t7 m! a
Homogeneity test, 齐性检验
7 H. U* O- [* A3 F$ \# N( w4 h: KHuber M-estimators, 休伯M估计量1 m: g3 {# e4 e
Hyperbola, 双曲线2 V6 T% q' x% ]7 l, ]9 f" W5 q6 x
Hypothesis testing, 假设检验$ _5 K' i1 g6 f l/ c( h5 i
Hypothetical universe, 假设总体
5 E. I: d; h* eImpossible event, 不可能事件6 Q1 c2 h9 M! }3 U# O
Independence, 独立性9 h; o. X8 @# q+ X, w1 c) U+ y6 X) u0 t$ g
Independent variable, 自变量
+ A) c; g! p' t, E" ? M4 NIndex, 指标/指数: f! J6 f) T- L5 w7 \: `8 J
Indirect standardization, 间接标准化法
5 C: J5 u" `( |3 K9 j; @Individual, 个体. t* `6 U( @8 U2 C) T8 E
Inference band, 推断带9 U/ k& p3 X3 Q* Q
Infinite population, 无限总体- Q7 y/ O1 i4 R" v, \ M: X
Infinitely great, 无穷大
% D4 ^ X; u! [& jInfinitely small, 无穷小
" ]9 u: n! p- o, H: W+ [- pInfluence curve, 影响曲线& Q! {& H8 g, O; e
Information capacity, 信息容量4 u8 O# V/ p# Y' `
Initial condition, 初始条件
2 w1 n7 C( v( f) E: y7 {5 s0 CInitial estimate, 初始估计值 y) V7 M. b" q ]1 t- B: R: v
Initial level, 最初水平' c0 e y5 k! m$ c5 H2 }4 j. W2 e+ x( G
Interaction, 交互作用- ` _$ k# l9 W r9 w+ v2 Z' g
Interaction terms, 交互作用项
2 L: N/ o4 E( G6 N$ {Intercept, 截距) H* Q& x7 c0 @3 U8 B& O
Interpolation, 内插法& e. E& S. P+ d' \' D; j3 V% R- X$ \
Interquartile range, 四分位距
" j- r+ r! H" LInterval estimation, 区间估计4 H9 b1 o" {0 V3 w: c
Intervals of equal probability, 等概率区间
9 U" n. e7 J8 e" f1 P. z; J( \( TIntrinsic curvature, 固有曲率* A \- P4 }/ X( v6 K) ]
Invariance, 不变性2 Y' h1 v3 a* @+ B) a
Inverse matrix, 逆矩阵. k5 L7 x9 r& O; n
Inverse probability, 逆概率# O; N! r% A$ X$ Y" J: C- N
Inverse sine transformation, 反正弦变换
% z: G6 h* U. V8 rIteration, 迭代
4 @+ o" t7 e8 C; u- rJacobian determinant, 雅可比行列式
4 {2 f+ O0 W: \9 N! z5 h: q7 cJoint distribution function, 分布函数- W F3 }! {- W' _) q
Joint probability, 联合概率
v7 p; S# T/ T# Z: iJoint probability distribution, 联合概率分布
1 t1 j" _7 ~0 [5 u: Q1 w+ tK means method, 逐步聚类法
. m; N' ^# `: M+ d0 h2 c2 Y* D( sKaplan-Meier, 评估事件的时间长度
* o) \8 m6 ?: }6 C! hKaplan-Merier chart, Kaplan-Merier图
' N% |7 ^/ I6 _( @9 v: a5 h4 X5 W' u# MKendall's rank correlation, Kendall等级相关
' E& T `2 e! n( Z' F: F, uKinetic, 动力学
' q* n; Q; j, o, _/ |6 d5 qKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
1 j7 H' m7 K. B' u. w$ _Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
& m: m9 U0 S- f$ J6 Q) mKurtosis, 峰度
8 g" d6 A# S1 k s }Lack of fit, 失拟3 a# B& K; a+ O6 |! N) h
Ladder of powers, 幂阶梯1 h9 ^( F1 [: `9 T% H9 j
Lag, 滞后. V- G8 [ I0 _
Large sample, 大样本2 Q! `2 V" T- \4 m
Large sample test, 大样本检验
Z6 W- e# j8 pLatin square, 拉丁方7 j6 M! C; d3 X6 V) B; i& ]/ Y
Latin square design, 拉丁方设计
- z( M' d+ D( K8 @+ DLeakage, 泄漏
9 g9 x, Z0 o+ {2 D5 m& Y# RLeast favorable configuration, 最不利构形1 ^- \( W6 d: q/ Z8 H9 P3 [! y: f
Least favorable distribution, 最不利分布
; z0 b7 m7 s; i/ V# b+ K5 RLeast significant difference, 最小显著差法4 y0 p* z( @9 d' @. m: b
Least square method, 最小二乘法% m( n: A. _' A5 i( O& J0 v) o
Least-absolute-residuals estimates, 最小绝对残差估计9 X5 j) k& C4 M
Least-absolute-residuals fit, 最小绝对残差拟合# }& R0 c- E9 @! k
Least-absolute-residuals line, 最小绝对残差线
, B, E: K% m8 P3 d" P. o6 X% VLegend, 图例. y# K; z6 g. n4 N
L-estimator, L估计量
8 q% m) v6 t7 s2 KL-estimator of location, 位置L估计量
( d J) [! U6 b* i9 h' C* LL-estimator of scale, 尺度L估计量# X7 K8 ~5 J7 R' n7 n
Level, 水平4 \5 _- Q: k" b- }+ {+ m {9 e- l3 [
Life expectance, 预期期望寿命
1 h4 L6 c% a% k2 e" [% bLife table, 寿命表
- T% z7 L% N0 g1 _) m# iLife table method, 生命表法
+ {) }0 R: H$ N5 r1 N! D) i3 t, iLight-tailed distribution, 轻尾分布; C& z: e; s; V
Likelihood function, 似然函数
" h7 v1 M) `# i: V, OLikelihood ratio, 似然比5 x, ]9 B+ U1 O- g; R0 v6 x
line graph, 线图
/ U2 z0 D- I' v; O1 ZLinear correlation, 直线相关6 X* Z6 t' @2 V' c
Linear equation, 线性方程
" z$ C5 ?" ~* k' x. Q9 K" W5 WLinear programming, 线性规划! S7 B& h- T Y. v% G$ L
Linear regression, 直线回归
' G' j' ? A( b8 C+ R+ BLinear Regression, 线性回归
8 h& D2 C" H9 |+ m. D3 ]Linear trend, 线性趋势+ @! T' |$ ]$ Y1 Y+ H' B
Loading, 载荷
3 u; U B4 x2 F( ULocation and scale equivariance, 位置尺度同变性4 G A4 o! Z7 a4 h, f) J% p8 F
Location equivariance, 位置同变性
; t6 F E. C8 H) j- XLocation invariance, 位置不变性
j% l8 K+ T( p; M* S( M2 o; ~" ?Location scale family, 位置尺度族
$ F6 Q2 M1 Z1 W% p( v) h) CLog rank test, 时序检验 * p7 `( [/ n+ Q+ r$ k8 U
Logarithmic curve, 对数曲线
+ d2 ]- p2 w3 i- j$ O; Q1 aLogarithmic normal distribution, 对数正态分布
) J5 M$ S u: O! U/ X. ELogarithmic scale, 对数尺度
& a0 [7 Q; O5 @! S& s5 ]5 S. g+ LLogarithmic transformation, 对数变换
1 q8 H" G5 s; x8 I( oLogic check, 逻辑检查7 K6 O) \$ d T! a
Logistic distribution, 逻辑斯特分布
' T% } g$ |" G8 |; L3 yLogit transformation, Logit转换
& B) [& Z* a/ eLOGLINEAR, 多维列联表通用模型 ) w' z b9 y: b: ]0 t: d
Lognormal distribution, 对数正态分布
) Y- V+ S0 c5 J9 oLost function, 损失函数
4 f; {% _2 C+ RLow correlation, 低度相关
4 H7 u- ~+ n- R1 h; DLower limit, 下限
* {: I7 M6 k& \& KLowest-attained variance, 最小可达方差, A5 F3 p- C8 k8 Q8 U
LSD, 最小显著差法的简称
0 G7 \1 X8 i: t' s0 e* mLurking variable, 潜在变量% d- ^0 g- i" U+ R, `
Main effect, 主效应
) r) V- G: Z" W( x2 M ]' |9 SMajor heading, 主辞标目
5 h ^+ a- A# o, T9 Y6 IMarginal density function, 边缘密度函数
3 E5 k/ C H; |. ] wMarginal probability, 边缘概率
+ W. u2 o q+ c8 ^ h vMarginal probability distribution, 边缘概率分布. ], v9 x6 }, p
Matched data, 配对资料) N" K, z# B1 a& z9 w9 n
Matched distribution, 匹配过分布
" z% U- [( g1 |+ @# Y# CMatching of distribution, 分布的匹配, m. q. ~0 J/ H, f0 r b) G
Matching of transformation, 变换的匹配( {: G/ p: L2 v6 O/ }
Mathematical expectation, 数学期望/ i( t7 T5 m' ]. ?5 c. I
Mathematical model, 数学模型
* p- _+ j( \. b6 X! GMaximum L-estimator, 极大极小L 估计量
; q" l4 {$ }& o0 |Maximum likelihood method, 最大似然法- g- e! R/ n) I$ n8 B
Mean, 均数
2 q' r9 J4 g2 T z% eMean squares between groups, 组间均方. x r/ U' a; y$ [
Mean squares within group, 组内均方! [. b& e5 Z$ |+ J5 [4 S" `" g
Means (Compare means), 均值-均值比较% P: K/ S) E4 J# [- Q/ P: a
Median, 中位数
: X6 {! |0 w* m" KMedian effective dose, 半数效量
& z" o( S+ f2 ~% l$ I3 z: YMedian lethal dose, 半数致死量* w+ ` y# t6 u3 L' F
Median polish, 中位数平滑
3 J; v+ s; ^3 D5 vMedian test, 中位数检验8 G9 I; O: l* j. C2 v' U+ J3 W
Minimal sufficient statistic, 最小充分统计量
! O* f/ {9 k* Q& T* W" s4 o) H3 S# ZMinimum distance estimation, 最小距离估计
4 Z0 G& @( {6 G: w: Z% v9 EMinimum effective dose, 最小有效量
* f* \- I! p5 w' F J3 ]Minimum lethal dose, 最小致死量; V8 f0 u7 t# S( y) K
Minimum variance estimator, 最小方差估计量) B N! m% ^# a
MINITAB, 统计软件包
+ q4 {2 y+ ?. EMinor heading, 宾词标目" H6 m C& W( v% k' \4 D+ Z
Missing data, 缺失值
) O' C+ t. @5 `# {Model specification, 模型的确定
3 P6 H5 y" P7 M4 lModeling Statistics , 模型统计
/ h' i5 g+ t U( m' gModels for outliers, 离群值模型
3 y3 P6 X) E5 [% T/ TModifying the model, 模型的修正
7 C0 A% R8 y# {3 s LModulus of continuity, 连续性模
4 i7 S! y" L. @% nMorbidity, 发病率 + n @6 a) L. x
Most favorable configuration, 最有利构形
) I6 }& n: G# t0 i7 ~% xMultidimensional Scaling (ASCAL), 多维尺度/多维标度- }* K, @" R' L( k( p( H
Multinomial Logistic Regression , 多项逻辑斯蒂回归
* w, M+ h. Q0 `% P5 [. G( l# TMultiple comparison, 多重比较+ E- }1 t {& G+ h
Multiple correlation , 复相关
+ M G* A" i" t. @; `7 x! \3 ^! qMultiple covariance, 多元协方差
6 K( [: K @1 j, ~5 J4 M% C5 @Multiple linear regression, 多元线性回归
" H" k6 s# i5 j+ Y9 P/ \9 yMultiple response , 多重选项* g% |2 X+ y$ C# H4 j1 e
Multiple solutions, 多解! B3 j0 `* [# u9 W: n- ]7 j2 \
Multiplication theorem, 乘法定理( {+ ]) Z( V/ g& k& l
Multiresponse, 多元响应
* S3 U+ s; c( i0 D! A- X' t6 NMulti-stage sampling, 多阶段抽样
5 q3 Z" {) s$ s7 M5 D# Z% q+ RMultivariate T distribution, 多元T分布
2 V/ w6 g% B. O$ N1 PMutual exclusive, 互不相容# ~% P4 g9 w1 i$ ^" B
Mutual independence, 互相独立& P% L+ ~0 X) d; ] h4 \
Natural boundary, 自然边界
0 w; _1 L, v8 {( t9 z5 f9 ~; r0 ZNatural dead, 自然死亡
% C! c i+ l+ s& y, p$ g; aNatural zero, 自然零' l4 F0 W7 m8 X, |5 H* M
Negative correlation, 负相关
2 Z* w2 X- ?5 r6 ANegative linear correlation, 负线性相关
% Z8 }+ c1 Q. q: R( W3 u) g2 x1 hNegatively skewed, 负偏, z+ ?$ M$ f1 ? q( @. D# d
Newman-Keuls method, q检验
% D% E0 g; f- _3 q7 ZNK method, q检验
5 C! b! u% k; `0 e" @No statistical significance, 无统计意义) s/ n) f1 A3 g/ g9 z/ F$ u. h. {9 q
Nominal variable, 名义变量
' z. T! I. B& L c! b3 g, `Nonconstancy of variability, 变异的非定常性
$ v5 ~% n$ {5 S" J- fNonlinear regression, 非线性相关
. j* W9 p6 u0 Z- d* z4 \Nonparametric statistics, 非参数统计
( p$ X& `) p6 l2 n; u+ RNonparametric test, 非参数检验( ]# [+ \" l9 J; o& t% u7 ~( C# Z) A
Nonparametric tests, 非参数检验
0 m0 i0 _4 S' H: n6 k. E4 f% P# INormal deviate, 正态离差! ]6 V7 F( n# [$ y! h; J
Normal distribution, 正态分布
' Y q* F9 q. Q! uNormal equation, 正规方程组% m. Q! T* o9 w' b; i. ^
Normal ranges, 正常范围" V% {: n# p! r) }% c I! k
Normal value, 正常值
' L; F# U0 }$ M+ @5 a: Y! zNuisance parameter, 多余参数/讨厌参数/ s: I+ ?" p# {+ u5 [0 [+ F
Null hypothesis, 无效假设 & n. N7 L9 [5 e
Numerical variable, 数值变量
9 x$ z; L1 K% z0 MObjective function, 目标函数. z) \- f# a; {: L
Observation unit, 观察单位* Q; q; @! U+ u4 G
Observed value, 观察值- N5 p+ i3 K- N" P: a! g0 o' l
One sided test, 单侧检验
9 t# a$ Q5 x3 ~3 t0 \ H4 r5 r/ xOne-way analysis of variance, 单因素方差分析- i9 {; w- o' m4 L, |
Oneway ANOVA , 单因素方差分析# @, \2 c6 v2 o. R
Open sequential trial, 开放型序贯设计" E) }3 x E: b g8 { a
Optrim, 优切尾5 v* Z. n0 M, D7 F8 c- x0 B! V/ [
Optrim efficiency, 优切尾效率4 e/ U) y7 ]" ^, A g8 ]
Order statistics, 顺序统计量3 r# w$ d) ?' ^/ I9 g2 f' |
Ordered categories, 有序分类
' [9 V, r) w, h/ u* @# U) T+ BOrdinal logistic regression , 序数逻辑斯蒂回归6 m, _( {% e+ S& L- o
Ordinal variable, 有序变量8 U# l2 B' j! m
Orthogonal basis, 正交基
" z0 }* l/ y" W4 KOrthogonal design, 正交试验设计
6 B6 \% I# s2 S* fOrthogonality conditions, 正交条件* u/ @- u5 b! _% D) f7 A/ B4 n2 B
ORTHOPLAN, 正交设计
) R$ Q1 S( h2 Y5 ]+ s* i% o3 }Outlier cutoffs, 离群值截断点
9 |: I! j' D* S: s! oOutliers, 极端值
, n# [' y# \# g2 e3 u- ~' M* xOVERALS , 多组变量的非线性正规相关
5 a/ W1 T( w( U6 YOvershoot, 迭代过度
/ X% T: v2 M( k" v ~Paired design, 配对设计! y3 H, J. E! N9 j
Paired sample, 配对样本
) W$ R) d" `( W* KPairwise slopes, 成对斜率
: n3 g: s2 _9 nParabola, 抛物线
( m8 X# a$ S4 Y5 e z- c EParallel tests, 平行试验
" ~7 G1 }/ r: d- k! Y& j$ |Parameter, 参数( q8 }( ]0 A7 i) H) C$ I
Parametric statistics, 参数统计; |- j" i- w {, K. h3 w
Parametric test, 参数检验
# t7 @% p8 j0 t: OPartial correlation, 偏相关
) j4 A+ V1 r0 F! C: IPartial regression, 偏回归
4 t8 R0 Z2 _! m ]9 g* C, FPartial sorting, 偏排序
v! V; y3 F$ C/ J# jPartials residuals, 偏残差1 i+ D' J0 x+ C0 o5 u4 \
Pattern, 模式: Q& B f7 J" y# ?# d1 I S( P- I
Pearson curves, 皮尔逊曲线: ~; G0 l ~6 j! i; F _
Peeling, 退层
) d% G( z" k, k% IPercent bar graph, 百分条形图4 t: ~6 w5 \$ j3 R' Z2 S) D
Percentage, 百分比
. K4 Z( o; ~! p% R. j% LPercentile, 百分位数
8 s/ \; l2 l) E9 \- q, ePercentile curves, 百分位曲线' [* T4 C$ q: d9 F
Periodicity, 周期性
3 L4 o2 S! N# J) uPermutation, 排列+ d r1 n; t' G$ G! V
P-estimator, P估计量. ~9 N* h" @* N% {' R. X
Pie graph, 饼图
4 r* l$ C8 |3 gPitman estimator, 皮特曼估计量4 s- Z6 l/ p5 Q$ U# Z. E
Pivot, 枢轴量
2 c9 [6 I: o5 G2 D# q3 Y( pPlanar, 平坦
8 E: V6 h5 p* o J6 k5 iPlanar assumption, 平面的假设
" X3 a3 c/ a+ t9 j' M! N/ n9 cPLANCARDS, 生成试验的计划卡# }- _% L" F; u6 i$ |
Point estimation, 点估计
9 @+ F/ M* g: d5 s1 U: x6 J1 R. S" aPoisson distribution, 泊松分布% A4 P9 B/ K6 z3 ~
Polishing, 平滑
! T }* p" l2 i# _Polled standard deviation, 合并标准差
1 F6 {1 N5 K1 F2 U9 b* P7 v1 NPolled variance, 合并方差0 @' ?2 b) U1 y2 {! ~
Polygon, 多边图: s {$ ^" _0 b2 ^. i
Polynomial, 多项式, f0 l" ?- M0 A1 O( H
Polynomial curve, 多项式曲线
7 A! ?7 i: p0 s- W* v( g) [! V# iPopulation, 总体
0 t3 |& r3 B( d, _2 M$ Y& }/ uPopulation attributable risk, 人群归因危险度
1 A1 S2 _- n% M/ @- TPositive correlation, 正相关0 H \" Z" i% ?9 V$ M
Positively skewed, 正偏6 G3 [1 R) a- b
Posterior distribution, 后验分布# N, K1 N7 y7 G1 j, O# M0 t
Power of a test, 检验效能. u, e- q( R0 y6 b
Precision, 精密度
/ b. X9 g9 U8 Y- }5 k! [0 KPredicted value, 预测值
8 j% ?% Q+ W7 h5 A( x5 U$ h" qPreliminary analysis, 预备性分析
4 V% H+ f7 X0 q+ dPrincipal component analysis, 主成分分析
- m p4 y4 B4 z: O# n! yPrior distribution, 先验分布7 K. y$ A6 [; I& k$ ~9 o5 f
Prior probability, 先验概率
7 {; T7 c/ J' O- E. h0 }Probabilistic model, 概率模型
! C8 Y- a7 D8 m+ H8 p! Nprobability, 概率- `7 ?4 i0 v3 N6 _ M& ]5 y
Probability density, 概率密度0 z6 F& e9 G. @8 w
Product moment, 乘积矩/协方差! v6 ~5 W5 ?# P- k& [! v1 _
Profile trace, 截面迹图' D* R4 ~% z" c2 I% e; M6 ~, o' f" m
Proportion, 比/构成比$ c7 J$ y& t. V; g# g4 C8 X, \
Proportion allocation in stratified random sampling, 按比例分层随机抽样8 W3 l' g |; f3 o+ h8 w7 [# }
Proportionate, 成比例
# K" S0 y1 T& p1 ^& P" o' ^" {4 UProportionate sub-class numbers, 成比例次级组含量" ]5 G. G9 D2 J% I, G4 v
Prospective study, 前瞻性调查
; {2 m, {; T& R3 u; [/ ?Proximities, 亲近性 3 ~; A$ E v. {: X! s5 f& l2 Q
Pseudo F test, 近似F检验0 a. C2 _! Z- C# ~1 ^
Pseudo model, 近似模型
+ H0 g' D' `- n" hPseudosigma, 伪标准差- l. n4 @8 _/ X: H
Purposive sampling, 有目的抽样 d9 O8 ?% }% q5 F- ^9 O
QR decomposition, QR分解/ j/ Z6 j/ x4 X9 S. K- l
Quadratic approximation, 二次近似
6 L6 S2 Q G; f2 W# w# EQualitative classification, 属性分类: ^2 P2 t& k% {
Qualitative method, 定性方法& y u) u; Y% g }0 \+ k% Y
Quantile-quantile plot, 分位数-分位数图/Q-Q图3 C" q; d9 G7 K% P! z
Quantitative analysis, 定量分析
" [1 k- e0 B) U0 y$ U7 gQuartile, 四分位数( q. D' \/ J( L# |( `! K
Quick Cluster, 快速聚类! b* F2 G& h2 \" R( z* @* B- u
Radix sort, 基数排序. g, r8 y2 V* C) ]9 f0 }
Random allocation, 随机化分组
+ o# ?4 v9 }0 uRandom blocks design, 随机区组设计
) r$ N8 ^8 M+ k$ Q! D, DRandom event, 随机事件
0 ?4 r3 D$ v D w9 p2 k' fRandomization, 随机化7 ~' D! B6 h/ p( a
Range, 极差/全距
/ \, n! F: c2 _Rank correlation, 等级相关0 n4 L g S+ g1 E6 G8 [
Rank sum test, 秩和检验, X" S; [, ^) @4 h1 f; o; }
Rank test, 秩检验 P5 b6 G- S) ?# `/ D" D Y
Ranked data, 等级资料2 A3 h7 Q/ ?& f* u* z, G! v
Rate, 比率
$ [6 s; E7 L: a+ M7 gRatio, 比例
4 Q. c7 `* m* e& _Raw data, 原始资料5 ~( z1 J# f$ u( z
Raw residual, 原始残差
$ {; d2 t1 _( U; s' z9 hRayleigh's test, 雷氏检验
' a0 M1 [' D4 NRayleigh's Z, 雷氏Z值
4 [4 H; w8 u/ Z2 H4 ^- OReciprocal, 倒数" o6 H3 M4 F& a7 V; s$ I Z6 t; D
Reciprocal transformation, 倒数变换 _4 G% S! I+ @! r; D
Recording, 记录
& c' A# t- ?+ s% C5 o/ {Redescending estimators, 回降估计量
2 F; G" z0 r' R2 I. e4 g- AReducing dimensions, 降维! G0 I0 Y7 \; G' u; [4 Y3 u1 ]
Re-expression, 重新表达1 H6 W7 P0 P- Z0 G' Y" X
Reference set, 标准组
# }0 `; a9 i! x9 r* IRegion of acceptance, 接受域
0 }! t: L. D' T! k$ ~- T) JRegression coefficient, 回归系数4 i$ U3 ~. i" I |. K6 Z
Regression sum of square, 回归平方和
7 G0 [/ o1 d' ^/ v# c mRejection point, 拒绝点
- h7 r) O) X/ d1 l* y) s5 {Relative dispersion, 相对离散度
* {% t! z, ^2 U) i# C! BRelative number, 相对数
) {5 A! N4 P; e8 P$ F9 f: k; S) q, FReliability, 可靠性
% n6 d8 u6 F8 w7 p6 rReparametrization, 重新设置参数! f) I2 m: b0 h# m C" [
Replication, 重复, u, d. b) N, p. ]: V; ~
Report Summaries, 报告摘要9 C4 B+ b( {" R$ }0 I3 J# y* f( Y
Residual sum of square, 剩余平方和
$ _6 m3 Q: }* e$ aResistance, 耐抗性
S8 ~: | E R8 r1 _4 b' C* }4 KResistant line, 耐抗线2 c1 H3 u! t' c6 O$ t0 R: ~
Resistant technique, 耐抗技术
1 ]) @8 }! a: e% wR-estimator of location, 位置R估计量! M, Z7 n3 |, K3 S7 @
R-estimator of scale, 尺度R估计量! w) ~ w) N4 y1 V! q
Retrospective study, 回顾性调查
" e) M, P% R3 c% s' r4 n0 sRidge trace, 岭迹0 P0 r/ H6 j- I) v
Ridit analysis, Ridit分析
- p0 M4 r: w1 L( I' LRotation, 旋转* C ~3 `) u) D' A4 M: P
Rounding, 舍入
% S0 |% y- W# s( O( c* }7 NRow, 行 { ^2 C, {. N. g
Row effects, 行效应4 U; F1 E2 N' B; q
Row factor, 行因素
4 T) G- s' O$ R& qRXC table, RXC表% r+ G* r" v* d
Sample, 样本# Q) A6 I) ^1 F5 R0 r ?
Sample regression coefficient, 样本回归系数8 Q' o' ]4 h3 w! B
Sample size, 样本量$ @! |; D' C- c% b( o" {
Sample standard deviation, 样本标准差
) ] l% Y; `. E `5 R( oSampling error, 抽样误差 Q% H5 H, v2 B2 O' Z
SAS(Statistical analysis system ), SAS统计软件包! L& q A* Y6 x$ l
Scale, 尺度/量表
! E. V* k: s* j+ B0 D0 {7 aScatter diagram, 散点图! |% h" a/ p- g0 Q( G: L7 d
Schematic plot, 示意图/简图 ^% g8 `9 r6 X
Score test, 计分检验) W$ B* X8 m# c& [* I. K
Screening, 筛检
. {. J# _7 r) Y" Q, f) d' HSEASON, 季节分析 3 m0 p* z: J* j2 s6 s
Second derivative, 二阶导数5 o K3 a: }: s8 U& K, v
Second principal component, 第二主成分) }( H/ F' |. d1 S
SEM (Structural equation modeling), 结构化方程模型 : o: E% J- F# S
Semi-logarithmic graph, 半对数图( r4 I" w4 V: Y1 k2 e- J' x# ^4 u
Semi-logarithmic paper, 半对数格纸 x, `: p1 Y, c/ \& c0 o6 U, h
Sensitivity curve, 敏感度曲线
5 h$ z9 i" h8 ~Sequential analysis, 贯序分析& P; V! J6 P/ x+ |' {# s
Sequential data set, 顺序数据集! I) ]- d, Q' q
Sequential design, 贯序设计6 i" B& w1 L# L6 S; [ C
Sequential method, 贯序法! D$ O( T3 P/ j9 E {4 \# {
Sequential test, 贯序检验法. |% @6 e5 f, P* b M
Serial tests, 系列试验
( E$ K3 K% ]8 W: {+ |2 NShort-cut method, 简捷法
9 u& j9 Q) y8 D! RSigmoid curve, S形曲线
7 y2 V; P7 N2 G7 g' a YSign function, 正负号函数 _5 `+ I1 U2 S; u" l9 w G) r
Sign test, 符号检验, {- Z: J; h5 j2 b2 [6 y
Signed rank, 符号秩5 W: k$ k# W- P1 F3 J
Significance test, 显著性检验
0 l) e+ i' X% P- S- s6 ISignificant figure, 有效数字
4 V! Q% d" Y9 [0 Y8 `Simple cluster sampling, 简单整群抽样
9 w F# C$ x" f9 E dSimple correlation, 简单相关
* k( _# a( K1 j& b& \Simple random sampling, 简单随机抽样0 X9 |" g1 ?' G7 m
Simple regression, 简单回归! G# [1 _# e0 B! B" c3 X0 S
simple table, 简单表
9 r: O+ S' u4 ~ p# YSine estimator, 正弦估计量
! b d; x: ]3 x2 {* M" z" gSingle-valued estimate, 单值估计- D. H8 @) I% o' W/ H
Singular matrix, 奇异矩阵& B# d! X q" P4 ~6 N/ u! U+ y
Skewed distribution, 偏斜分布' v/ d9 n( ?9 R) `" a5 A8 O
Skewness, 偏度7 [9 Z- f4 k% m7 e6 k' C
Slash distribution, 斜线分布
+ i$ ]6 i" Z5 @! vSlope, 斜率
, g2 N |) O) n) CSmirnov test, 斯米尔诺夫检验
: t0 f3 Q# B0 B% _. [# h. Q! h \$ g9 MSource of variation, 变异来源
. j8 f" g) C% E9 R$ k& j" }+ F! oSpearman rank correlation, 斯皮尔曼等级相关
1 M" b5 w& u5 p. s6 f! ESpecific factor, 特殊因子
1 N5 t. Q3 {. mSpecific factor variance, 特殊因子方差) s3 [, ?+ ^4 h3 a5 t
Spectra , 频谱+ q2 G8 L6 T7 R& Z9 D. D' |
Spherical distribution, 球型正态分布
% b J `/ I6 L1 f; O/ wSpread, 展布5 [0 g" `1 h. P: c9 ^& K
SPSS(Statistical package for the social science), SPSS统计软件包) f! Z7 S2 x$ f2 f) s8 J4 l
Spurious correlation, 假性相关2 H0 R e& X, m
Square root transformation, 平方根变换
* U( L+ M' b' ^: W( ^1 n0 X- J; LStabilizing variance, 稳定方差6 e4 c. [; C, e
Standard deviation, 标准差
6 X9 y/ D6 a# H- g# YStandard error, 标准误
) A) K6 [' Q9 gStandard error of difference, 差别的标准误
' ?% B& u8 ^& p& h+ s# a0 P- h# MStandard error of estimate, 标准估计误差
: c& e6 X% Z, H, eStandard error of rate, 率的标准误/ U1 Q" O: |: n7 Z" d
Standard normal distribution, 标准正态分布
( z3 |( _% {! J( M) `" l! a! OStandardization, 标准化
: G! c/ t* ?1 i x: J) TStarting value, 起始值( X' ^7 D2 Z3 M1 C, R6 b' Y
Statistic, 统计量+ \* n& Q* Q$ |+ O, h J
Statistical control, 统计控制
# x4 s. s! Y% F' e+ }) BStatistical graph, 统计图9 G) K0 y" J* Z* ^: K% E! l- O
Statistical inference, 统计推断8 y3 [: {; W! T: ?( W) S
Statistical table, 统计表2 @2 J+ J- E3 b# Z1 {
Steepest descent, 最速下降法
& |" F0 `: i( d' cStem and leaf display, 茎叶图1 L( l# D+ d& j9 X# h
Step factor, 步长因子4 X( |2 E4 d: o9 K
Stepwise regression, 逐步回归
9 d# S* F/ u [: g, d+ _* wStorage, 存! ?+ _, `! ~( ~$ r, K$ @
Strata, 层（复数）
6 S3 t7 ]- X! M; s/ \" q) YStratified sampling, 分层抽样
" ~# f9 p+ Z, m' K6 |5 y2 }( Z1 WStratified sampling, 分层抽样% Y7 l5 T" _, B" K0 t
Strength, 强度
" w: K% D, G0 ` j+ [' `/ ~2 ~Stringency, 严密性: }; e0 {- Q+ m3 _$ w
Structural relationship, 结构关系
|8 O, q* I P& d& C cStudentized residual, 学生化残差/t化残差7 j) [% n1 s# m# P$ T
Sub-class numbers, 次级组含量& \; v+ \2 u; G
Subdividing, 分割. y8 w" V+ ?; f+ L! F# j
Sufficient statistic, 充分统计量. y: _$ k9 p1 P6 J
Sum of products, 积和
( }/ p# n V3 y# W& L0 a1 LSum of squares, 离差平方和" Y: ~" S# B$ Y- [& ]; S" n$ x
Sum of squares about regression, 回归平方和, C: o1 q! F u: Q/ W
Sum of squares between groups, 组间平方和& @. `: i9 }" E9 T: F! j Y
Sum of squares of partial regression, 偏回归平方和
4 w/ a- v% I8 I, rSure event, 必然事件/ B& F# E) M8 ~7 f, z
Survey, 调查. Q+ d0 C' f7 U+ I: a% `) W
Survival, 生存分析6 M4 L5 {2 k+ p) s
Survival rate, 生存率& n* a* j( [/ Q7 i# n0 j$ O
Suspended root gram, 悬吊根图- ]! }& v4 I5 Y( v% ?) a
Symmetry, 对称
- a- f4 e3 B, Z- T) e& q. Y7 ESystematic error, 系统误差; e, e$ X- j+ H* w. r n! i& K
Systematic sampling, 系统抽样* b0 ^% ]% g5 E- d0 n( o; s4 M
Tags, 标签 W: `$ `# G+ w4 H* v: f, {. S [
Tail area, 尾部面积8 Y, o! a" ~( e) y
Tail length, 尾长
* s0 Y L5 U0 l8 l TTail weight, 尾重
7 ]! q! _3 g1 ?6 Q8 @ \Tangent line, 切线/ \+ L3 E5 D5 J/ n/ D! U, W: Z
Target distribution, 目标分布+ k8 f3 w) p6 e7 {* E) C6 |
Taylor series, 泰勒级数: p% Q# B! }- _7 L2 H" k
Tendency of dispersion, 离散趋势$ X/ E+ c* a( g/ r" K" Z. `$ I
Testing of hypotheses, 假设检验7 T0 W4 ~% N! `2 \
Theoretical frequency, 理论频数9 h1 N+ S. z+ o8 z1 x
Time series, 时间序列
% ]- h; n$ p0 S. Z1 RTolerance interval, 容忍区间$ J- p3 V1 x5 b7 z& p# V4 @
Tolerance lower limit, 容忍下限
4 P M- O8 q# ?! NTolerance upper limit, 容忍上限' H g1 B k! N
Torsion, 扰率
! H) p: x' H8 \ n/ MTotal sum of square, 总平方和
9 B/ n* _! Z) YTotal variation, 总变异
9 T; `. U x$ b6 a& kTransformation, 转换5 \1 v! q) C) D4 z! @% M8 [3 E
Treatment, 处理
3 _, {: i& X+ CTrend, 趋势+ e( p6 n$ o2 y9 t! `
Trend of percentage, 百分比趋势- V: ]" B& p4 f: a T$ Z* G
Trial, 试验% _; D9 f8 X+ W9 M! E3 h l4 K
Trial and error method, 试错法
7 c; z. i3 \' k- c8 q: k) bTuning constant, 细调常数1 E+ r% k) g! D+ _- L( \1 j r
Two sided test, 双向检验7 _+ H) j( f" M+ o
Two-stage least squares, 二阶最小平方3 v( K2 K, p# ]" x
Two-stage sampling, 二阶段抽样: I( u0 u6 I/ }9 v# J: m7 w
Two-tailed test, 双侧检验
2 o% f# B2 _6 Z BTwo-way analysis of variance, 双因素方差分析- \" D0 { V/ P1 x' a0 a! M: o' b7 D
Two-way table, 双向表' i* A" p" @+ ]. P `& k& V3 Q
Type I error, 一类错误/α错误
9 v6 a9 e/ J, IType II error, 二类错误/β错误
( I: n' g9 G' A' H' GUMVU, 方差一致最小无偏估计简称; G L8 t8 x4 ^% b
Unbiased estimate, 无偏估计 I6 w, w' z+ x- k% h- t. R
Unconstrained nonlinear regression , 无约束非线性回归
. D; F- a8 F3 ~8 m7 w# XUnequal subclass number, 不等次级组含量2 ]& ~/ [9 R, y" B u6 R9 E( x
Ungrouped data, 不分组资料
. l6 T0 O3 E9 U* @0 BUniform coordinate, 均匀坐标3 o/ ?$ [* s0 E/ U- F
Uniform distribution, 均匀分布
2 y3 W2 ^6 X9 n0 a z4 g3 W; gUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
; y j- k1 a9 a9 O$ LUnit, 单元
# m8 Y" F3 z% u4 S$ C/ @! n) r0 EUnordered categories, 无序分类
% H- S( f+ \+ A( Q/ `Upper limit, 上限
9 I2 w p0 }8 Y7 L% J6 D pUpward rank, 升秩
9 s; }( r5 I2 @. ^3 @* I# ?Vague concept, 模糊概念
+ t+ z. e" |# O3 Z& HValidity, 有效性
6 X) X! X/ a0 ]0 X bVARCOMP (Variance component estimation), 方差元素估计5 m N; e' X3 X: \# ^
Variability, 变异性: j) h$ N# a/ C& t% L2 `( M
Variable, 变量6 u" G/ ]2 o$ q7 M- t
Variance, 方差
, b( X$ l) W" w9 k$ xVariation, 变异
6 H' t* j+ A1 iVarimax orthogonal rotation, 方差最大正交旋转
" y/ G9 S% } |$ n: x4 xVolume of distribution, 容积
- G; F+ [6 h; j0 j1 o( KW test, W检验
% c; W9 h% K0 Q8 {! a! AWeibull distribution, 威布尔分布0 O- j, o& o( H
Weight, 权数
9 _' T7 T: ?8 b1 @! qWeighted Chi-square test, 加权卡方检验/Cochran检验) O# n; g1 s9 ?! c7 b1 n8 p
Weighted linear regression method, 加权直线回归! L. j- O' G0 G- q" c2 J
Weighted mean, 加权平均数
" \4 x% M$ R8 z3 a' cWeighted mean square, 加权平均方差
# T6 I$ W1 P- p$ {- f( n- l& DWeighted sum of square, 加权平方和1 o! Z# t3 g& T9 A. Y5 q# V
Weighting coefficient, 权重系数
0 R/ x) U' j6 |. S* r$ j* z0 |Weighting method, 加权法
+ I8 o* B! `: ^; j- c+ X) yW-estimation, W估计量' a. p" k( G5 ~( U6 \: o. h
W-estimation of location, 位置W估计量$ Z. h) S3 _; m
Width, 宽度# C2 n9 y8 @3 p2 X1 T- b+ Y# R2 N# D
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
, t1 O; y" I( A5 G5 O6 r& FWild point, 野点/狂点
, Z6 f5 h- y W# T5 @8 lWild value, 野值/狂值0 O- d$ F& M; o/ s3 |$ w
Winsorized mean, 缩尾均值" n9 t7 Q5 q7 D5 }: s/ R1 `. i* _
Withdraw, 失访 $ i+ K0 j( R) p( |5 D
Youden's index, 尤登指数6 H" O0 b7 ]1 p7 k/ [
Z test, Z检验( R( S9 C6 \% ^! {* K+ q! {/ X% U0 G8 |
Zero correlation, 零相关0 _9 b8 S9 Z8 j5 I) l7 Z
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
